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sysid - System Identification in R

The package provides functions for constructing mathematical models of dynamic systems from measured input-output data. It lets you create and use models of dynamic systems not easily modeled from first principles or specifications. You can use time-domain and frequency-domain input-output data to identify discrete-time input-output models, transfer functions and state space models.

Installation

You can install sysid from github using the devtools package.

require(devtools)
install_github("surajy123/R-sysid/")

Note: Windows users need to install the Rtools executable from https://cran.r-project.org/bin/windows/Rtools/

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Version

Install

install.packages('sysid')

Monthly Downloads

157

Version

1.0.4

License

GPL-3

Last Published

January 7th, 2017

Functions in sysid (1.0.4)

detrend

Remove offsets and linear trends
compare

Compare the measured output and the predicted output(s)
dataSlice

Subset or Resample idframe data
estpoly

Estimated polynomial object
fitch

Fit Characteristics
cstr_mis

Continuous stirred tank reactor data with missing values
%=%

Multiple assignment operator
getcov

Parameter covariance of the identified model
frd

Frequency response data
etfe

Estimate empirical transfer function
inputNames<-

Extract or set series' names
impulseest

Estimate Impulse Response Coefficients
idinput

function to generate input singals (rgs/rbs/prbs/sine)
iv

ARX model estimation using instrumental variable method
idfrd

S3 class constructor for storing frequency response data
idframe

S3 class for storing input-output data.
impulseplot

Impulse Response Plots
nInputSeries

Number of series in input or output
inputData

Output or Input-data
iv4

ARX model estimation using four-stage instrumental variable method
optimOptions

Create optimization options
residplot

Plot residual characteristics
misdata

Replace Missing Data by Interpolation
sim

Simulate response of dynamic system
read.idframe

Data input into a idframe object
read.table.idframe

Read the contents of a table-formatted file
predict.estpoly

Predictions of identified model
rarx

Estimate parameters of ARX recursively
spa

Estimate frequency response
step

Step Response Plots
plot.idframe

Plotting idframe objects
time

Sampling times of IO data time creates the vector of times at which data was sampled. frequency returns the number of damples per unit time and deltat the time-interval between observations
plot.idfrd

Plotting idfrd objects